Basic Machine Learning Concepts in Python

          Module 1: Python Fundamentals

Section 1: Introduction to Python
- Lesson 1: What is Python?
  Module 1, Section 1, Lesson 1: What is Python?
- Lesson 2: Installing Python
  Module 1, Section 1, Lesson 2: Installing Python

Section 2: Basic Python Syntax
- Lesson 1: Python Syntax Essentials
  Module 1, Section 2, Lesson 1: Python Syntax Essentials
- Lesson 2: Variables and Data Types
  Module 1, Section 2, Lesson 2: Variables and Data Types

Section 3: Python Tools and Environment
- Lesson 1: Using an IDE
  Module 1, Section 3, Lesson 1: Using an IDE
- Lesson 2: Running Python Code
  Module 1, Section 3, Lesson 2: Running Python Code

Section 4: Simple Operations in Python
- Lesson 1: Arithmetic Operations
  Module 1, Section 4, Lesson 1: Arithmetic Operations
- Lesson 2: Input and Output
  Module 1, Section 4, Lesson 2: Input and Output

Section 5: Control Structures Basics
- Lesson 1: If Statements in Python
  Module 1, Section 5, Lesson 1: If Statements in Python
- Lesson 2: Loops with Python
  Module 1, Section 5, Lesson 2: Loops with Python


Module 2: Data and Problem Understanding

Section 1: Introduction to Data
- Lesson 1: What is Data?
  Module 2, Section 1, Lesson 1: What is Data?
- Lesson 2: Types of Data
  Module 2, Section 1, Lesson 2: Types of Data

Section 2: Data Collection Basics
- Lesson 1: Sources of Data
  Module 2, Section 2, Lesson 1: Sources of Data
- Lesson 2: Simple Data Collection Techniques
  Module 2, Section 2, Lesson 2: Simple Data Collection Techniques

Section 3: Introduction to Problem Solving
- Lesson 1: Identifying Problem Statements
  Module 2, Section 3, Lesson 1: Identifying Problem Statements
- Lesson 2: Breaking Down Problems into Steps
  Module 2, Section 3, Lesson 2: Breaking Down Problems into Steps

Section 4: Getting to Know Simple Datasets
- Lesson 1: Exploring Sample Datasets
  Module 2, Section 4, Lesson 1: Exploring Sample Datasets
- Lesson 2: Reading Data with Python
  Module 2, Section 4, Lesson 2: Reading Data with Python

Section 5: Data Visualization Fundamentals
- Lesson 1: Introduction to Data Visualization
  Module 2, Section 5, Lesson 1: Introduction to Data Visualization
- Lesson 2: Creating Simple Charts
  Module 2, Section 5, Lesson 2: Creating Simple Charts


Module 3: Simple Machine Learning Concepts

Section 1: What is Machine Learning?
- Lesson 1: Defining Machine Learning
  Module 3, Section 1, Lesson 1: Defining Machine Learning
- Lesson 2: Machine Learning in Everyday Life
  Module 3, Section 1, Lesson 2: Machine Learning in Everyday Life

Section 2: Basic Concepts in Machine Learning
- Lesson 1: Training and Testing Overview
  Module 3, Section 2, Lesson 1: Training and Testing Overview
- Lesson 2: Features and Labels
  Module 3, Section 2, Lesson 2: Features and Labels

Section 3: Algorithms at a Glance
- Lesson 1: Simple Algorithm Concepts
  Module 3, Section 3, Lesson 1: Simple Algorithm Concepts
- Lesson 2: Understanding Overfitting
  Module 3, Section 3, Lesson 2: Understanding Overfitting

Section 4: Introduction to Classification
- Lesson 1: What is Classification?
  Module 3, Section 4, Lesson 1: What is Classification?
- Lesson 2: Simple Classification Example
  Module 3, Section 4, Lesson 2: Simple Classification Example

Section 5: Introduction to Regression
- Lesson 1: What is Regression?
  Module 3, Section 5, Lesson 1: What is Regression?
- Lesson 2: Basic Regression Example
  Module 3, Section 5, Lesson 2: Basic Regression Example


Module 4: Building Simple Models in Python

Section 1: Dataset Preparation Basics
- Lesson 1: Splitting Data into Training and Testing
  Module 4, Section 1, Lesson 1: Splitting Data into Training and Testing
- Lesson 2: Preparing Data in Python
  Module 4, Section 1, Lesson 2: Preparing Data in Python

Section 2: Creating a Simple Model
- Lesson 1: Building a Model with Python
  Module 4, Section 2, Lesson 1: Building a Model with Python
- Lesson 2: Understanding Model Components
  Module 4, Section 2, Lesson 2: Understanding Model Components

Section 3: Evaluating Model Performance
- Lesson 1: Introduction to Accuracy
  Module 4, Section 3, Lesson 1: Introduction to Accuracy
- Lesson 2: Confusion Matrix Basics
  Module 4, Section 3, Lesson 2: Confusion Matrix Basics

Section 4: Tuning a Simple Model
- Lesson 1: Basic Model Tuning Concepts
  Module 4, Section 4, Lesson 1: Basic Model Tuning Concepts
- Lesson 2: Testing Model Parameters
  Module 4, Section 4, Lesson 2: Testing Model Parameters

Section 5: Improving Model Performance
- Lesson 1: Simple Strategies for Improvement
  Module 4, Section 5, Lesson 1: Simple Strategies for Improvement
- Lesson 2: Model Evaluation and Iteration
  Module 4, Section 5, Lesson 2: Model Evaluation and Iteration


Module 5: Projects in Machine Learning Basics

Section 1: Project Overview and Planning
- Lesson 1: Understanding the Project
  Module 5, Section 1, Lesson 1: Understanding the Project
- Lesson 2: Planning Steps for a Project
  Module 5, Section 1, Lesson 2: Planning Steps for a Project

Section 2: Data Collection for Your Project
- Lesson 1: Gathering Your Data
  Module 5, Section 2, Lesson 1: Gathering Your Data
- Lesson 2: Exploring Your Data
  Module 5, Section 2, Lesson 2: Exploring Your Data

Section 3: Developing Your Model
- Lesson 1: Building Your Project Model
  Module 5, Section 3, Lesson 1: Building Your Project Model
- Lesson 2: Testing Your Model
  Module 5, Section 3, Lesson 2: Testing Your Model

Section 4: Presenting Your Findings
- Lesson 1: Creating a Simple Report
  Module 5, Section 4, Lesson 1: Creating a Simple Report
- Lesson 2: Sharing Your Results
  Module 5, Section 4, Lesson 2: Sharing Your Results

Section 5: Final Review and Next Steps
- Lesson 1: Reviewing Your Project Work
  Module 5, Section 5, Lesson 1: Reviewing Your Project Work
- Lesson 2: Next Steps in Machine Learning
  Module 5, Section 5, Lesson 2: Next Steps in Machine Learning